Construction Robots Improve Productivity

Robots help us to work more constructively in construction

As the saying goes, insanity is doing the same thing over and over again and expecting a different result. Whether or not this is true, it involves keeping track of the process in hand. In large and complicated projects, however, this is easier said than done. Take the construction industry. Human workers don’t always do exactly as they’ve been told, costing project managers valuable time and money. Small errors can snowball into problems further down the line, and delayed completion dates incur a range of other expenses.

Fundamentally, if we want to do things better, we need to know where we are going wrong. If progress can be accurately monitored in detail, and errors quickly identified, then we stand a good chance of improving productivity. There are few places this is more valuable than in construction. One startup has brought in robots to help review construction site progress and keep projects running on schedule and according to budget.

Sticking to the schedule

For a construction project to work as forecasted, every member involved in the process needs to achieve their goals according to the schedule. Perhaps unsurprisingly, this hardly ever happens. In fact, productivity rates in construction are shockingly poor. According to statistics published by KPMG in 2015 on the global construction industry, only 25 per cent of projects came within 10 per cent of their original deadlines in the past three years. As the size of the project increases, productivity only gets worse. Since construction plans and timelines are intrinsically linked to budgets, this has a knock on effect on costs for all involved.

If construction progress can be closely monitored in a detailed way then managers stand a better chance of improving productivity. This will provide a much needed shot in the arm for an industry whose growth has stalled globally for decades. Traditionally, construction sites are monitored by humans who make regular inspections. Silicon Valley startup Doxel, however, has come up with a better way.

The robot inspector has arrived

Doxel’s autonomous robots are fitted with the laser detection system LIDAR. When work has finished for the day, the robot independently navigates and scans the entire project site. This data is then sent to the cloud, where deep learning AI algorithms process the work that has been done. If anything is out of place, or if something hasn’t been properly installed, then these algorithms raise the alarm, enabling the Doxel team to flag up issues to construction managers.

In a pilot study conducted on a medical building in California, daily scans by the Doxel robot led to huge improvements in project management. According to the Doxel team, use of their AI technology saw a 38 per cent increase in labour productivity. The overall project also came in at 11 per cent under budget. Whilst these figures pertain to only one site, any improvements are welcome in an industry that is plagued by missed deadlines and spiralling costs.

Are we all about to be replaced?

Doxel’s intelligent technology encapsulates just the kind of issue that humans worry about with robots: losing their jobs to automation. If a robot can do the job of a human more cheaply and more effectively, then the human worker had better think of an alternative occupation fast. There is a certain level of nuance to the above example, however. Doxel’s construction site monitoring robots are not there to change what human workers do, but to help them to do it better. This kind of process optimisation has value in all industrial sectors, not only construction. With minor intervention, it is clear that robots can drastically increase productivity and profits. They are a simple solution to an issue which has held back global construction for years.

Are robot inspectors the solution to the productivity crisis in construction? Are there any other potential applications for this technology? Could your business benefit from intelligent monitoring? Comment below with any thoughts and comments.

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